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In this paper, we address an instance of the dynamic capacitated multi-item lot-sizing problem (CMILSP) typically encountered in steel rolling mills. Production planning is carried out at the master production schedule level, where the various end items lot sizes are determined such that the total cost is minimised. Through incorporating the various technological constraints associated with the manufacturing process, the integrated production-inventory problem is formulated as a mixed integer bilinear program (MIBLP). Typically, such class of mathematical models is solved via linearisation techniques which transform the model to an equivalent MILP (mixed integer linear program) at the expense of increased model dimensionality. This paper presents an alternative branch-and-bound based algorithm that exploits the special structure of the mathematical model to minimise the number of branches and obtain the bound at each node. The performance of our algorithm is benchmarked against that of a classical linearisation technique for several problem instances and the obtained results are reported. [ABSTRACT FROM AUTHOR]

This paper is devoted to serial production lines consisting of producing and inspection machines that obey the Bernoulli reliability and Bernoulli quality models. Such production lines are encountered in automotive assembly and painting operations where the downtime is relatively short and the defects are due to uncorrelated random events. For these systems, this paper develops analytical methods for performance analysis, bottleneck identification, and design. In addition, insights into the nature of bottlenecks in such systems are provided, and an empirical rule for placing an inspection machine that maximises the production rate of non-defectives is formulated. [ABSTRACT FROM AUTHOR]

The paper studies a layout problem of variable number of ellipses with variable sizes placed into an arbitrary disconnected polygonal domain with maximum packing factor. The ellipses can be continuously translated and rotated. Restrictions on the dimensions of the ellipses are taken into account. Tools for the mathematical modelling of placement constraints (distance constraints between ellipses and containment of ellipses into a polygonal domain) using the phi-function technique are introduced. The tools make it possible to formulate the layout problem in the form of MIP model that is equivalent to a sequence of nonlinear programming subproblems. We develop a new solution algorithm that involves the feasible starting point algorithm and optimisation procedure to search for efficient locally optimal solutions of the layout problem. This algorithm can be used in the design of parts for «support-free» additive manufacturing, taking into account the conditions for its static/ dynamic strength. Results of the algorithm implementation for a topologically optimised flat part with the analysis of a stress state are provided. [ABSTRACT FROM AUTHOR]

This paper deals with lot sizing decisions in a flexible job shop manufacturing system considering dependencies between lot sizing decisions. A novel mathematical model is developed to optimise lot sizing and scheduling simultaneously using a product-oriented approach as opposed to the job-oriented approach which has been prevalently considered in the literature. Moreover, the proposed model considers further underlying assumptions such as assembly operations, sequence-dependent setup times, initial inventory and safety stock levels, as well as lots with unequal and variable sizes. The objective is to minimise the total production, setup, and tardiness penalty costs of the system. To solve the formulated problem, a self-adaptive Cuckoo Optimisation Algorithm (COA) embedded with three new immigration mechanisms is developed. Numerical experiments are conducted to demonstrate the validity of the model and investigate the efficiency and effectiveness of the employed optimisation algorithm. [ABSTRACT FROM AUTHOR]

The advent of globalisation has led to the growing use of global virtual teams (GVT) for software development. The use of such teams enables organisations to operate across national, economic and social, and cultural boundaries; this new form of teamwork presents challenges for traditional coordination mechanisms. Hence, a range of new operational problems for the coordination of software development teams have emerged due to the nature of virtual work: these are related to issues of geographical distance, language differences, time zone(s) differences, cultural differences, and trust. This paper applies a theoretical model drawn from prior research to explore the coordination mechanisms employed by a global virtual software development team in a major multi-national telecommunications organisation. The study analyses the impact that the aforementioned issues have on the effectiveness of project team coordination mechanisms and then develops a refined conceptual model to guide future research on global virtual software development teams. The findings also inform practice on the problems encountered in ensuring the effective coordination of such teams. [ABSTRACT FROM AUTHOR]

Atherosclerosis is a leading cause of death worldwide; it emerges as a result of multiple dynamical cell processes, including hemodynamics, endothelial damage, innate immunity and sterol biochemistry. Making matters worse, nearly 463 million people have diabetes, which increases atherosclerosis-related inflammation, diabetic patients are twice as likely to have a heart attack or stroke. The pathophysiology of diabetic vascular disease is generally understood. Dyslipidemia with increased levels of atherogenic low-density lipoprotein, hyperglycemia, oxidative stress and increased inflammation are factors that increase the risk and accelerate development of atherosclerosis. In a recent paper, Xie [Well-posedness of a mathematical model of diabetic atherosclerosis. J Math Anal Appl. 2022;505(2):125606], we have developed a mathematical model that includes the effect of hyperglycemia and insulin resistance on plaque growth. In this paper, we propose a more comprehensive mathematical model for diabetic atherosclerosis which include more variables; in particular, it includes the variable for Advanced Glycation End-Products (AGEs) concentration. Hyperglycemia trigger vascular damage by forming AGEs, which are not easily metabolized and may accelerate the progression of vascular disease in diabetic patients. The model is given by a system of partial differential equations (PDEs) with a free boundary. We also establish the local existence and uniqueness of solution to the model. The methodology is to reduce the free boundary to a fixed boundary and the system of PDEs to an abstract evolution equation in Banach spaces, and apply the theory of analytic semigroup. [ABSTRACT FROM AUTHOR]

Drawing from original and best practice research, this article proposes a model for teaching social work students how to practice with refugees using Bronfenbrenner's ecological model as a guide. Social workers globally must be prepared across the social work curriculum with best practice research and recommendations that keep pace with the largest refugee crisis the world has ever known. This article proposes a teaching framework based on empirical data, social work scholarship, and information on refugee needs and best practice approaches. [ABSTRACT FROM AUTHOR]

The model of recovery is based on an individualized and personalized journey of change and growth that is recognized both to be socially supported and mediated and to be contextually bound in terms of community resources and assets (as well as barriers and challenges in the local community). Specificity and precision has been added to recovery models by the emerging concept of 'recovery capital' creating not only the potential for a recovery metric but also the opportunity to assess changes in three key components of recovery capital (personal, social and community) and how they influence and shape each other. The paper builds on this by suggesting that not only can recovery capital have a residual impact on the community but that our understanding of this approach can be significantly enhanced with reference to John Braithwaite's model of macro-criminology and in particular the concept of ink spots to explain spread. The paper integrates the contagion ideas of recovery with the cascade effects Braithwaite describes to explain crime reductions and concludes with a discussion of the potential of concepts like collective efficacy and social contagion to be used to supplement public health approaches to the implementation of recovery-oriented interventions at a systems level. While there has been a huge growth in the 'evidence base' around recovery in recent years, there remain two primary gaps that this paper attempts to address. The first is around the paucity of conceptual frameworks and models for recovery and the second is around recovery as a social and community phenomenon. In this paper, we build on previous work by the authors and supplement it with inter-disciplinary work around a 'big picture' model of recovery communities and recovery spread. [ABSTRACT FROM AUTHOR]

In this paper, we discuss mathematical modeling opportunities that can be included in an introductory Differential Equations course. In particular, we focus on the development of and extensions to the single salty tank model. Typically, salty tank models are included in course materials with matter-of-fact explanations. These explanations miss the opportunity for students to develop rate of change equations for themselves. In this paper, we highlight an open-ended single salty tank task that provides the foundation for more complicated salty tank models that we also detail herein. Furthermore, we discuss instructional implementation techniques that instructors can use in their classes to meet their specific learning goals. [ABSTRACT FROM AUTHOR]

This paper investigates the co-ordination of order quantities amongst the players in a four-level supply chain with a centralised decision process. The first level of the supply chain consists of multiple buyers, the second level of a vendor (manufacturer), the third level consists of multiple tier-1 suppliers, and the fourth level consists of multiple tier-2 suppliers. Each supplier supplies one or more items that are components of the product produced by the manufacturer. The model developed in this paper guarantees that the local costs for the players either remain the same as before co-ordination, or decrease as a result of co-ordination. A mathematical model is developed, with numerical examples presented and results discussed. [ABSTRACT FROM AUTHOR]

The paper presents a multi-disciplinary decentralized integrated modeling approach (DIMA) for comprehensive modeling production and logistics networks. The DIMA allows the implementing of the principle of throughout modeling 'conceptual model → mathematical model → software'. In the paper, the DIMA is illustrated on the problem of collaborative network (CN) dynamical synthesis and reconfiguration. This problem is described in a comprehensive way on the conceptual and mathematical levels. This description allows interlinking synthesis and analysis issues of CN planning and control taking into account system elements' activity, uncertainty factors, and structure dynamics. The paper reports a novel approach for comprehensive multi-disciplinary modeling distributed large-scale business systems with decentralized decision-making and control. In this paper, the main features of the DIMA are summarized based on recently developed partial models and algorithms for a large spectrum of CN management issues. [ABSTRACT FROM AUTHOR]

One of the most common systems in non-automated warehouses, is drive-in pallet racking with a shared storage policy (which is usually based on the duration-of-stay). Such scheme targets towards an efficient use of storage space, since its operation costs are directly related to the size and layout of the warehouse. In this paper, two mathematical programming models and two greedy-randomised based heuristics for finding (nearly) optimal storage and retrieval operation sequences for this type of storage system are proposed. The computational effectiveness of the proposed approaches is measured by considering two sets of synthetic instances. The obtained results show that the proposed heuristics are not only able to compute high-quality solutions (as observed when being compared with the optimal solutions attained by the mathematical programming models), but it is also capable of providing solutions in very short running times even for large instances for which the mathematical programming model failed to find feasible solutions. At the light of these results, the best heuristic is also tested using a rolling-horizon planning strategy in a real-world case study, obtained from a Chilean company. It turns out that the attained results are more effective than the company's current storage policy. [ABSTRACT FROM AUTHOR]

This paper considers the problem of minimising makespan on a single batch processing machine with flexible periodic preventive maintenance. This problem combines two sub-problems, scheduling on a batch processing machine with jobs' release dates considered and arranging the preventive maintenance activities on a batch processing machine. The preventive maintenance activities are flexible but the maximum continuous working time of the machine, which is allowed, is determined. A mathematical model for integrating flexible periodic preventive maintenance into batch processing machine problem is proposed, in which the grouping of jobs with incompatible job families, the starting time of batches and the preventive maintenance activities are optimised simultaneously. A method combining rules with the genetic algorithm is proposed to solve this model, in which a batching rule is proposed to group jobs with incompatible job families into batches and a modified genetic algorithm is proposed to schedule batches and arrange preventive maintenance activities. The computational results indicate the method is effective under practical problem sizes. In addition, the influences of jobs' parameters on the performance of the method are analyzed, such as the number of jobs, the number of job families, jobs' processing time and jobs' release time. [ABSTRACT FROM AUTHOR]

In recent years, the interests of disassembly line have increased owing to economic reasons and the increase of environmental awareness. Effective line can provide many advantages in terms of economic aspect and it facilitates competition the companies with others. This study contributes to the relevant literature by a branch, bound and remember algorithm for disassembly line balancing problem with AND/OR precedence. The proposed exact solution method employs the memory-based dominance rule to eliminate the reduplicated sub-problems by storing all the searched sub-problems and to utilise cyclic best-first search strategy to obtain high-quality complete solutions fast. In this paper, minimising the number of stations is taken as the performance measure. The proposed methodology is tested on a set of 260 instances and compared with the mathematical model using CPLEX solver and five well-known metaheuristics. Computational results show that the proposed method is capable of obtaining the optimal solutions for all the tested instances with less than 0.1 seconds on average. Additionally, comparative study demonstrates that the proposed method is the state-of-the-art algorithm and outperforms the CPLEX solver and metaheuristics in terms of both solution quality and search speed aspects. [ABSTRACT FROM AUTHOR]

This paper focuses on an identical parallel machine scheduling problem with minimising total tardiness of jobs. There are two major issues involved in this scheduling problem; (1) jobs which can be split into multiple sub-jobs for being processed on parallel machines independently and (2) sequence-dependent setup times between the jobs with different part types. We present a novel mathematical model with meta-heuristic approaches to solve the problem. We propose two encoding schemes for meta-heuristic solutions and three decoding methods for obtaining a schedule from the meta-heuristic solutions. Six different simulated annealing algorithms and genetic algorithms, respectively, are developed with six combinations of two encoding schemes and three decoding methods. Computational experiments are performed to find the best combination from those encoding schemes and decoding methods. Our findings show that the suggested algorithm provides not only better solution quality, but also less computation time required than the commercial optimisation solvers. [ABSTRACT FROM AUTHOR]

This paper presents a quasi-optimal inspection policy for equipment that is leased for a given period and whose failures can be detected only through inspections. Maintenance including inspections and replacements is entrusted to the lessor. Whenever inspection reveals that the equipment is in failed state, it is replaced (or restored to a state as good as new). In case the average downtime between failures and their detection exceeds a contractual pre-specified duration, a penalty is incurred by the lessor. The proposed mathematical model and numerical algorithm allow finding a quasi-optimal sequence of inspection instants (θ1*, θ2*, ... , θN*) which minimises the expected total cost incurred by the lessor over the lease period L. A numerical example is presented and the obtained results are discussed. We investigate numerically the effect of the variation of the downtime penalty cost, the inspection cost, the lease period length, and the equipment reliability on the quasi-optimal inspection policy to be adopted by the lessor. [ABSTRACT FROM AUTHOR]

This paper considers the design and balancing of mixed-model disassembly lines with multi-robotic workstations under uncertainty. Tasks of different models are performed simultaneously by the robots which have different capacities for disassembly. The robots have unidentical task times and energy consumption respectively. Task precedence diagrams are used to model the precedence relations among tasks. Considering uncertainties in disassembly process, the task processing times are assumed to be interval numbers. A mixed-integer mathematical programming model is proposed to minimise the cycle time, peak workstation energy consumption, and total energy consumption. This model has a significant managerial implication in real-life disassembly line systems. Since the studied problem is known as NP-hard, a metaheuristic approach based on an evolutionary simulated annealing algorithm is developed. Computational experiments are conducted and the results demonstrate the proposed algorithm outperforms other multi-objective algorithms on optimisation quality and computational efficiency. [ABSTRACT FROM AUTHOR]

This paper studies production lines composed of several serial machines which are subject to random operation-dependent failures. The production lines have no intermediate buffers between adjacent machines. Machines have different deterministic processing times. The purpose of this paper is to propose analytical models to assess steady-state availability and throughput of such lines. Thousands of production line configurations have been experimented to compare the performance of the proposed approach to approximate existing techniques. A general simulation model was developed and statistical tests carried out to prove that the proposed approach is exact and robust to model unreliable, unbuffered, and non-homogeneous production lines. [ABSTRACT FROM AUTHOR]

This paper deals with the objective of determining an optimal part sequence on a single-stage multifunctional machining system (SSMS) with a view to achieve the broad objectives of cost minimization and time minimization. SSMS has become a preferred alternative for manufacturers to use the resource efficiently, owing to the flexibility and process variety offered by it. This paper formulates a mathematical model that considers the minimization of both set-up cost and time simultaneously. The option of hiring an additional fixture has also been considered that enables the reduction in tool magazine replenishment and re-fixturing operations, which in turn offers economic advantage by way of reducing set-up cost. This study has proposed a new heuristic by modifying the simulated annealing concept to solve the underlying problem. The conventional simulated annealing search scheme is replaced by a chaotic search that takes into account the ergodic and stochastic properties of chaotic systems. In order to restrict the premature convergence and to diversify the search space, a modified perturbation scheme has been employed. The performance of the proposed algorithm was tested on a simulated case study adopted from the literature and the results obtained reveal the effectiveness and scalability of the proposed algorithm. The results establish that the proposed approach is effective and reactive to severe disturbances and must take place in the manufacturing environment. [ABSTRACT FROM AUTHOR]

Extant research suggests the effectiveness of Occupational Health Psychology (OHP) interventions depends on their design in the broader organisational context. While the field recognises that pre- and posttest evaluation do not sufficiently capture the complex dynamics around OHP interventions, complex multi-level OHP interventions are still scarce in the literature. As established intervention implementation frameworks suggest, it remains difficult to address this complexity in practice. The present position paper re-evaluates lessons learned from two complex European OHP intervention projects, by applying the Integrated Process Evaluation Framework (IPEF) and related theories to bridge the gap between the theoretically recognised complexity and practical challenges. The re-evaluations emphasise that programme-multilevel theories rooted in OHP-perspectives contribute to adequately hypothesising around systemic factors and mechanisms relevant to OHP interventions. Concretely, middle range theories that outline how an intervention's mechanisms work within a specific context to produce certain outcomes are crucial. Additionally, strategically and actively involving key stakeholders at all levels of the system and across the different intervention phases improves the embedding of OHP interventions in organisations. We elaborate on these insights with seven concrete recommendations for complex OHP intervention research. [ABSTRACT FROM AUTHOR]

Continuous mode of adsorption using fixed bed column has been widely applied for wastewater treatment. Several dynamic mathematical models were used to analyze the adsorptive properties and breakthrough curve of the column system. This paper aims to highlight the underlying principles and applicability of three commonly used dynamic models, namely Thomas, Bohart-Adams and Yoon Nelson in estimating the behavior of continuous adsorption and its properties. The model equations were analyzed to unlock the root of derivation, and the findings from literature were summarized, compared and discussed. As opposed to the results from literature, it was revealed that the models studied are actually identical with direct relationships among the rate constants; hence, they must provide the same fitting regression. Three dynamic models were applied in a case study on column adsorption of rhodamine B by palm kernel shell activated carbon (surface area = 1775 m2/g), from which the results were presented and discussed by the analysis of breakthrough and fitting of dynamic models. The breakthrough time decreased with increasing initial dye concentration and flow rate, and vice-versa for bed height. The applicability of these dynamic models was demonstrated by the close agreement of qo from the models (33.9 mg/g − 69.3 mg/g) with the experimental ones (36.8 mg/g − 70.9 mg/g) with low percentage error. [ABSTRACT FROM AUTHOR]

Previous research examining comparison relations in word problems primarily focused on students' achievements in word problems with one operation. In this paper, we extend previous research to examine the achievement of students of different ages on word problems that integrate compare and combine word problems, hereafter referred to as 'compare-combine problems'. The convenience sample in this research consists of 96 second-grade, 103 fourth-grade, and 85 sixth-grade students from Belgrade, Serbia. The results indicate that 2nd, 4th and 6th graders have similar achievement on consistent language problems, but students in higher grades perform better on inconsistent language problems. We identified a type of problem that does not provide insight into students' understanding – problem in which the order of quantities follows the order of steps in problem solving. We emphasize the importance of using integrated problems of different structures in teaching, as well as in-depth work on understanding relational terminology. [ABSTRACT FROM AUTHOR]

This paper is concerned with the tensor sparse principal component analysis (TSPCA) by obtaining principal components which are linear combinations of a small subset of the original features for tensorial data. The core mathematical model can be formulated as a nonsmooth nonconvex optimization problem with a polynomial objective function, and with the sparsity constraint and the unit Euclidean spherical constraint. By employing the tools in tensor analysis, along with the variational properties for the involved $ \ell _{0} $ ℓ 0 -norm, the optimality condition of TSPCA is analysed in terms of stationary points. To well resolve the problem, we reformulate the stationary conditions into the Lagrange stationary equation system via the property of the projection operator onto the sparsity constraint set. With special emphasis on the Jacobian nonsingularity of the corresponding nonlinear system, we propose the Lagrange–Newton algorithm for pursuing the stationary point, which serves as a promising approximation of the optimal solution to TSPCA. The locally quadratic convergence rate is also established under mild conditions. Numerical experiments illustrate the effectiveness of our proposed TSPCA approach in terms of the solution accuracy as well as the computation time. [ABSTRACT FROM AUTHOR]

Working with approximations is a common practice in physics. This paper presents an exploratory study of student understanding of some of the elementary aspects of approximations encountered in college physics. For this purpose, a questionnaire (a set of 14 multiple-choice questions) was developed to probe how students dealt with these aspects in a variety of contexts. The questionnaire was finalized after a trial of its pilot version on 7 students on the basis of their written scripts and interviews. After content validation by three external experts, the test was administered to a sample of 141 senior undergraduate physics students from a diverse set of colleges and national institutes. Data analysis reveals several significant student pitfalls in the topic related principally to (i) the identification of a dimensionless ratio to characterize an approximation, (ii) the notion of the order of approximation and consistent handling of a problem up to the required order, and (iii) the notion of the order of infinitesimal in calculus-based derivations. The findings are of direct pedagogic relevance. [ABSTRACT FROM AUTHOR]

Fun and social affiliation are good predictors of long-term intention to use game-based interventions including those for motivating physical activity, yet current player matching algorithms are poor at facilitating social connectedness. In this paper, we report on the results of a study investigating how different player traits are associated with interest in social features of an exercise game for improving player experience through better player matching using common and complementary characteristics. Twelve conceptual scenarios were illustrated using storyboards and data was collected from 196 respondents who rated their attitudes and preferences towards gamification elements. Correlational results showed that all scenarios, except for cutting corners, were perceived as persuasive, enjoyable, engaging and are likely to increase future exercise intention for players who score high on Philanthropist- and Socialiser-oriented traits. Results also showed that many players favour the altruistic donation feature. Furthermore, qualitative results underscore that it is the player's partner that matters more than the players' personalities. We conclude with practical recommendations for designing more personalised exercise games that can include more socially engaging game mechanics in the future. [ABSTRACT FROM AUTHOR]

This paper investigates alcohol consumption within cultures of football fandom through the innovative combination of theories of the carnivalesque and Bourdieu's concepts of habitus, field, and capital. Focus groups (n = 79) were conducted with football supporters in England and Scotland. Semi-structured interviews (n = 15) were also conducted with key organizational stakeholders. Research explored the importance and role of alcohol consumption for supporters when watching or attending matches.. Participants confirmed the cultural significance, perceived normalcy and historical links between football and alcohol consumption. Supporters highlighted the importance of the sociability, friendship, and social capital aspects of alcohol consumption. Participants believed football supporters are perceived differently in comparison with supporters of other sports, arguing that legislation surrounding alcohol consumption at other sports allowed supporters to enhance the carnivalesque by drinking alcohol, whereas football fans were more restricted. Participants agreed the habitus of excessive drinking and violence associated with football supporters led to a bad reputation, however, this view was outdated. Participants also recognized a growing drug culture in football. The findings draw attention to the alcohol-sport relationship and the contested relations, and diverging interests and influences, within the social field of football. [ABSTRACT FROM AUTHOR]

The temperature dependency of the adsorption isotherm renders its significance as one of the primary input parameters in models dealing with moisture transport. The present study involved the determination of the adsorption isotherm of sixteen building materials from various categories, including cladding, building paper, wood, sheathing boards, and insulations. The measurements were conducted under nine climatic conditions, a combination of three temperatures (3 °C (37.4 °F), 21 °C (69.8 °F), 45 °C (113 °F)) and three relative humidity levels (50%, 70%, 90%). The study indicated that relative humidity increased the building materials' equilibrium moisture content (EMC). In opposition, an increase in temperature decreased the EMC of the tested materials. It was discovered that cellulose fiber and wood-based materials had a greater capacity to store moisture than others. Conversely, the minimum moisture content was observed in brick, Densglass gold gypsum, and EPS products. Furthermore, we used the ABC model as an adaptable mathematical equation for a novel nonlinear surface fitting of adsorption isotherms of tested materials to make optimal use of the experimental data and effectively analyze the simultaneous impact of all temperatures and relative humidities. Tested against the measured experimental data, we obtained the best R-squared values from the second-order polynomial Equation. [ABSTRACT FROM AUTHOR]

Virtual assembly is the simulation of parts assembly processes by computer, analysing, evaluating and optimizing the feasibilities and procedures of assembly. It can thus avoid the potential problems and risks from designing to assembling. In this way, we can achieve the global optimization of the products and timely respond to the needs of the market. This paper presents a modelling framework for virtual assembly paths design and optimization of two objects on the basis of a class of hybrid system, which is applicable in many manufacturing environments. We propose an elementary hybrid machine containing time-driven and event-driven dynamics. We describe in detail a method of assembly paths design. The objective of optimization is evaluated in terms of time in the transition dynamics so as to make the problem more tractable. An explicit algorithm for deriving optimal assembly policies is developed. The optimal results indicate the feasibility and efficacy of the model and control algorithms. [ABSTRACT FROM AUTHOR]

Scheduling problems concern the allocation of limited resources over time among both parallel and sequential activities. Load balancing has been adopted as an optimization criterion for several scheduling problems. However, in many practical situations, a load-balanced solution may not be feasible or attainable. To deal with this limitation, this paper presents a generic mathematical model of load distribution for resource allocation, called desired load distribution (DLD). The objective is to develop a DLD model for scheduling of unrelated parallel machines that can be used both in centralized resource management settings and in agent-based distributed scheduling systems. The paper describes the proposed DLD model in details, presents a dynamic programming based optimization algorithm for the proposed model, and then discusses its application to agent-based distributed scheduling. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to provide a review and comparison of the approaches to multi-criteria decision-making (MCDM) in the design of manufacturing cells. A brief description of existing classifications is provided, together with an overview on the MCDM. Selected papers are reviewed and a structured scheme is outlined which allows comparison of inputs, criteria, solution approaches and outputs across selected models. Finally the models are discussed and directions for new avenues of work are identified. [ABSTRACT FROM AUTHOR]

In this paper, we extend the Mickens' methodology to construct a second-order nonstandard finite difference (NSFD) method, which preserves dynamical properties including positivity, local asymptotic stability and especially, global asymptotic stability of a general single-species model. This NSFD method is based on a novel weighted non-local approximation of the right-hand side function in combination with the renormalization of the denominator function. The weight guarantees the dynamic consistency and the nonstandard denominator function ensures the convergence of order 2 of the NSFD method. The result is that we obtain a second-order and dynamically consistent NSFD method. It is proved that the NSFD method is simple and efficient and can be extended for solving a broad range of mathematical models arising in real-world applications. Also, we combine the constructed second-order NSFD method with Richardson's extrapolation technique to generate high-order numerical approximations. Finally, the theoretical findings are illustrated and supported by numerical experiments. [ABSTRACT FROM AUTHOR]

Coexisting serious illness and posttraumatic stress place hospitalized individuals at risk for complex pain, anxiety, and retraumatization. Hospital palliative care social workers increasingly recognize the value of trauma-informed care (TIC) for reducing harm in the inpatient setting. Despite this recognition, there is limited operationalization of TIC principles for inpatient interventions. This paper integrates each TIC principle with inpatient psychosocial interventions to advance trauma-informed competencies among inpatient palliative care social workers and to provide a foundation for future TIC implementation research. [ABSTRACT FROM AUTHOR]

In this paper, we contend with whether we still need traditional ethics education as part of healthcare professional training given the abilities of chatGPT (generative pre-trained transformer) and other large language models (LLM). We reflect on common programmatic goals to assess the current strengths and limitations of LLMs in helping to build ethics competencies among future clinicians. Through an actual case analysis, we highlight areas in which chatGPT and other LLMs are conducive to common bioethics education goals. We also comment on where such technologies remain an imperfect substitute for human-led ethics teaching and learning. Finally, we conclude that the relative strengths of chatGPT warrant its consideration as a teaching and learning tool in ethics education in ways that account for current limitations and build in flexibility as the technology evolves. [ABSTRACT FROM AUTHOR]

The goal of this paper is to study a mathematical model which describes the quasistatic frictional contact between aviscoplastic body and a foundation. The contact is modeled with normal compliance, unilateral constraint, friction, damage andmemory term, which also includes foundation memory property. We present the classical formulation of the problem and derivevariational-hemivariational formulation. Finally we provide a unique weak solution of the problem. [ABSTRACT FROM AUTHOR]

In this paper, the mathematical modeling of the novel corona virus (COVID-19) is considered. A brief relationship between the unknown hosts and bats is described. Then the interaction among the seafood market and peoples is studied. After that, the proposed model is reduced by assuming that the seafood market has an adequate source of infection that is capable of spreading infection among the people. The reproductive number is calculated and it is proved that the proposed model is locally asymptotically stable when the reproductive number is less than unity. Then, the stability results of the endemic equilibria are also discussed. To understand the complex dynamical behavior, fractal-fractional derivative is used. Therefore, the proposed model is then converted to fractal-fractional order model in Atangana-Baleanu (AB) derivative and solved numerically by using two different techniques. For numerical simulation Adam-Bash Forth method based on piece-wise Lagrangian interpolation is used. The infection cases for Jan-21, 2020, till Jan-28, 2020 are considered. Then graphical consequences are compared with real reported data of Wuhan city to demonstrate the efficiency of the method proposed by us. [ABSTRACT FROM AUTHOR]

Mathematical modeling is applied to study phenomena and system behavior.In various engineering fields, many physical phenomena are illustrated using a set of differential equations.In many real-world applications, the mathematical models are very complex, and numerical simulations in high-dimensional systems are challenging.Examples of these problems are large-scale physical problems such as geophysical, which have high temporal and spatial variations.In these problems, model order reduction is a useful method for achieving an appropriate approximation because it can significantly decrease computational costs.Deep learning has recently been used to explore information from data and make predictions.There are several methods for dimensionality reduction.In this paper, we combine the dynamic mode decomposition (DMD) and the long short-term memory (LSTM) network.This is because LSTM can predict nonlinear systems and time series data.We use LSTM and DMD to predict nonlinear systems and reduce dimensions, respectively.Four common DMD schemes have been applied for dimensionality reduction.The common geophysical dataset has been used to evaluate the performance of the proposed method.Finally, we compare the variations of the modal coefficients which are obtained from snapshots projection and the reduced-order model.These results show the high accuracy of our proposed method.One of the things that is important is the time complexity of algorithm implementation.The time complexity of the proposed method is 10 times faster when 15 modes are used for modeling than when all features are used. [ABSTRACT FROM AUTHOR]

This paper presents a nonlinear model of a novel three-dimensional oblique rotating friction seismic isolator (3D ORFSI). A quasistatic test of the device was conducted, and the results showed that devices processed a plump hysteretic loop in the vertical isolation direction, which agreed with the theoretical prediction. The effects of different parameters were evaluated using a mathematical model. The proposed mathematical model was then applied to assess the seismic response of an 8-story concrete-frame building with horizontal isolators and the 3D ORFSI. [ABSTRACT FROM AUTHOR]

'Rotation and shift' based diffusion functions are used in modern ciphers especially in ARX (Addition, Rotation, and XOR) based designs. They are preferred over other alternatives as they are efficient and lightweight. Usually, such diffusion functions map an n-bit block to another n-bit block. One of the requirements for an n-bit to n-bit diffusion function is that, it should be invertible. In this paper, we present mathematical models for different classes of 'rotation and shift' based diffusion functions and explore their invertibility. We derive sufficient conditions under which diffusion functions of these classes are invertible. [ABSTRACT FROM AUTHOR]

Composting is a complex bioprocess, requiring a lot of empirical experiments to optimize the process. A dynamical mathematical model for the biodegradation of the organic matter during the composting process has been developed. The initial organic matter expressed by chemical oxygen demand (COD) is decomposed into rapidly and slowly degraded compartments and an inert one. The biodegradable COD is hydrolysed and consumed by microorganisms and produces metabolic water and carbon dioxide. This model links a biochemical characterization of the organic matter by Van Soest fractionating with COD. The comparison of experimental and simulation results for carbon dioxide emission, dry matter and carbon content balance showed good correlation. The initial sizes of the biodegradable COD compartments are explained by the soluble, hemicellulose-like and lignin fraction. Their sizes influence the amplitude of the carbon dioxide emission peak. The initial biomass is a sensitive variable too, influencing the time at which the emission peak occurs. [ABSTRACT FROM AUTHOR]

A paper published by Anagnostopoulos et al. in volume 55 of the Hydrological Sciences Journal (HSJ) concludes that climate models are poor based on temporal correlation between observations and individual simulations. This interpretation hinges on a common misconception, that climate models predict natural climate variability. This discussion underlines fundamental differences between hydrological and climatological models, and hopes to clear misunderstandings regarding the proper use of climate simulations. Citation Huard, D. (2011) A black eye for the Hydrological Sciences Journal. Discussion of ‘A comparison of local and aggregated climate model outputs with observed data’ by G.G. Anagnostopoulos et al. (2010, Hydrol. Sci. J. 55 (7), 1094–1110). Hydrol. Sci. J. 56(7), 1330–1333. [ABSTRACT FROM PUBLISHER]

A major challenge in statistics is to make inferences in the presence of measurement error or mismeasurement variables. Such mismeasurements appear in various contexts such as econometrics, biology or medicine. The paper by Carroll, Chen and Hu is completely in line with this challenging task. In this context, I would like to express my sincere and great appreciation for their contribution to this topic. It is a great pleasure for me to have the opportunity to contribute a discussion of this paper. [ABSTRACT FROM AUTHOR]

M-ary baseband FSK modulated signals, which utilize M-set different frequencies, can be modelled as a set of complex rotating phasors. The received modulated signals can be detected by counting the speed and the direction of the complex phasor rotation. Conventional methods such as zero-crossing detection used this baseband FSK signal property. The detection approach presented in this paper is to count the number of quadrant crossing instead of zero crossing in a symbol period to demodulate FSK signals. Counting quadrant crossings acts as a noise filtering and improves the detection performance. The performance is improved further by using decision rules at fuzzy boundary and soft decision detection. The system modelling and simulation methods are illustrated in the paper. The performance comparison and improvement are shown by a 4-ary FSK signal example on wireless Rayleigh fading channels. [ABSTRACT FROM AUTHOR]

Active chilled beams (ACBs), as indoor air terminal units in heating, ventilation, and air conditioning (HVAC) systems, have been of great concern in recent years due to the requirements of energy savings and indoor thermal comfort. This paper reviews the structure and application of ACB, which is helpful in identifying current research scenarios and prospects. The results indicate that the structure of ACBs will be improved based on the entrainment ratio (ER), cooling performance and acoustic behavior as the manufacturing level evolves. The mathematical model of ACBs is constantly being optimized, although there is still room for simplification to fit practical applications. Research on airflow patterns and thermal comfort can be extended to larger spaces (including buildings with large sensible heat ratios) and various climates. Based on the optimization of the ACB mathematical model, modern control theory can be focused on the research on ACB control system. ACB system has a coupling trend with other systems to achieve the comprehensive utilization of energy due to the characteristics of high-temperature cooling. In addition, numerous technical issues remain to be resolved to reduce unnecessary energy consumption. These conclusions also provide a simple reference for research and design in the area where this technology is still in its infancy. [ABSTRACT FROM AUTHOR]

In this paper, the problem of maximizing the beamwidth with array antenna giving the desired minimum power gain in the wide-beam mainlobe is addressed. Termed this problem as Mainlobe BeamWidth Maximization (MBWM). This paper, by optimizing the gain pattern instead of optimizing the beam pattern, first sets up the mathematical model for the MBWM problem. It comes out that the MBWM problem is non-convex, hence cannot be solved effectively in polynomial time. To simplify the solving processes, the MBWM problem, thereafter, is converted into a series of power gain pattern synthesis (PGPS) problems. The bisection strategy together with the processing procedures for the PGPS problem are utilized to design an iterative algorithm to solve the MBWM problem. Numerical simulations compared with the existing methods which optimize the beam pattern are carried out. [ABSTRACT FROM AUTHOR]

This paper addresses the minimal makespan parallel machine problem where machines are subject to preventive maintenance events of a known deterministic duration. The processing time of a job depends on its predecessors since the machine’s last maintenance. The paper proposes some dominance criteria for sequences of jobs assigned to a machine, and uses these criteria to design constructive heuristics to this NP-hard problem. The computational investigation determines the parameters that make a hard instance and studies the sensitivity of the heuristics to these parameters. [ABSTRACT FROM AUTHOR]

Decentralised scheduling with dispatching rules is applied in many fields of production and logistics, especially in highly complex manufacturing systems. Since dispatching rules are restricted to their local information horizon, there is no rule that outperforms other rules across various objectives, scenarios and system conditions. In this paper, we present an approach to dynamically adjust the parameters of a dispatching rule depending on the current system conditions. The influence of different parameter settings of the chosen rule on the system performance is estimated by a machine learning method, whose learning data is generated by preliminary simulation runs. Using a dynamic flow shop scenario with sequence-dependent set-up times, we demonstrate that our approach is capable of significantly reducing the mean tardiness of jobs. [ABSTRACT FROM PUBLISHER]

The purpose of this paper is to develop and test intelligible heuristics for the scheduling of production orders that can easily be used in practice. Grounded in a case study, this paper examines the combined effects of assignment and sequencing heuristics on commonly used performance indicators. Discrete event simulation is used in the analysis to adequately capture the complexity found in the case study: production orders differing in many aspects, two unrelated parallel machines with varying and product-specific speed, and set-up times that depend on the (dis)similarity of successive orders. Evaluating 108 strategy–scenario combinations including the base case derived from the case study, it is found that a loading heuristic based on order quantity and scheduled capacity in combination with the shortest set-up heuristic performs best. When compared to the heuristic approach used by the case company, this strategy saves about 13.9% of total machine busy time and increases service level by 10.2%. In addition, using a reduced set of 40 production orders we are able to demonstrate that the best heuristic strategies comes close to results generated in a two-stage optimisation. The gap to optimality is only 3.1% in total busy time on average over all scenarios. [ABSTRACT FROM PUBLISHER]

In recent years, achieving high energy efficiency has become one of the primary goals in manufacturing, along with maintaining high productivity and quality. In many manufacturing systems, it is sometimes possible to temporarily switch off a machine to reserve energy, and switch it back on when a certain condition is met. Indeed, production control-based shop floor continuous improvement is recognised as one of the most cost-effective ways to achieve energy-efficient production. In this paper, we study serial production lines with Bernoulli machines and finite capacity buffers and assume that some of the machines in the line can be switched on and off during the production process according to a state-based feedback control policy. Mathematical models for the system under consideration are derived and analytical methods are developed for calculating the system performance measures during transients. Specifically, exact Markovian analysis is used for two- and three-machine lines in which the switch-on/off operations of only one machine is considered. For longer lines, the switch-on/off operations of multiple machines are considered and an aggregation-based approximation approach is applied to evaluate the system performance measures. Numerical experiments show that the method developed can be used to efficiently calculate the system’s performance with high accuracy. [ABSTRACT FROM PUBLISHER]

The Resource-Constrained Project Scheduling Problem (RCPSP) is one of the most intractable combinatorial optimisation problems that combines a set of constraints and objectives met in a vast variety of applications and industries. Its solution raises major theoretical challenges due to its complexity, yet presenting numerous practical dimensions. Adaptive memory programming (AMP) is one of the most successful frameworks for solving hard combinatorial optimisation problems (e.g. vehicle routing and scheduling). Its success stems from the use of learning mechanisms that capture favourable solution elements found in high-quality solutions. This paper challenges the efficiency of AMP for solving the RCPSP, to our knowledge, for the first time in the literature. Computational experiments on well-known benchmark RCPSP instances show that the proposed AMP consistently produces high-quality solutions in reasonable computational times. [ABSTRACT FROM AUTHOR]

In this paper, the extended Resource Renting Problem (RRP/extended) is presented. The RRP/extended is a time-constrained project scheduling problem, in which the total project cost is minimised. In the RRP/extended, this total project cost is determined by a number of extra costs, which are defined in this paper. These costs are based on the costs that are used in the traditional Resource Renting Problem and the Total Adjustment Cost Problem. Therefore, the RRP/extended represents a union of these two problems. To solve the RRP/extended, a scatter search is developed. The building blocks of this scatter search are specifically designed for the RRP/extended. We introduce two crossovers and an improvement method. The efficiency of these building blocks will be shown in the paper. Furthermore, a sensitivity analysis is presented in which the five costs have diverse values. [ABSTRACT FROM AUTHOR]